About Me

I am a fourth-year (2019-now) Ph.D. candidate in Computer Science and Engineering at the University of Notre Dame, and have the fortune to be advised by Prof. Meng Jiang. I also work closely with Dr. Chenguang Zhu from Microsoft Research. Before that, I received my bachelor degree of Computer Science and Technology at Sichuan University in 2019.

My primary research interest lies in natural language processing and machine learning. Specifically, I am working on using structured (e.g., knowledge graph) and unstructured (e.g., retrieved rext) knowledge to enhance language representation learning for open-domain question answering, commonsense reasoning and natural language generation tasks. I am also interested in using knowledge for better domain adaptation and few-shot learning.

My research is generously supported by Bloomberg Ph.D. Fellowship, Notre Dame Grad School Select Fellowship, Microsoft Research and National Science Foundation.

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What’s New!

  • [2023.01] One survey paper is accepted at EACL 2023 multi-task learning in NLP.
  • [2023.01] Two papers are accepted at ICLR 2023, on large language model for open-domain QA and multi-task pre-training.
  • [2022.11] Our paper “Empowering Language Models with Knowledge Graph Reasoning for Question Answering” [link] won the best paper award at SoCal NLP Symposium 2022! The paper is also accepted to EMNLP 2022!
  • [2022.11] Tutorial on Knowledge-augmented Methods for Natural Language Processing is accepted by WSDM 2023 in Singapore!
  • [2022.10] Five papers are accepted by EMNLP 2022, on question answering, commonsense reasoning and multi-task learning!
  • [2022.09] KnowledgeNLP-AAAI Workshop at AAAI 2023 is calling for papers: Knowledge Augmented Methods for NLP! Deadline: November 4, 2022.
  • [2021.05] I am thrilled to receive Bloomberg Ph.D. Fellowship! Thanks Bloomberg!


  • Email: wyu1 [at] nd [dot] edu
  • Office: 355 Fitzpatrick Hall of Engineering
  • Location: University of Notre Dame, Notre Dame, IN 46565